Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Jia Haipeng, jiahaipeng95@gmail.com
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
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// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
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// any express or implied warranties, including, but not limited to, the implied
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//M*/
#include "test_precomp.hpp"
#ifdef HAVE_OPENCL
using namespace cvtest;
using namespace testing;
using namespace std;
#define MAX_CHANNELS 4
PARAM_TEST_CASE(MergeTestBase, MatDepth, Channels, bool)
{
int type;
int channels;
bool use_roi;
//src mat
cv::Mat mat[MAX_CHANNELS];
//dst mat
cv::Mat dst;
// set up roi
int roicols, roirows;
int srcx[MAX_CHANNELS];
int srcy[MAX_CHANNELS];
int dstx, dsty;
//src mat with roi
cv::Mat mat_roi[MAX_CHANNELS];
//dst mat with roi
cv::Mat dst_roi;
//ocl dst mat for testing
cv::ocl::oclMat gdst_whole;
//ocl mat with roi
cv::ocl::oclMat gmat[MAX_CHANNELS];
cv::ocl::oclMat gdst;
virtual void SetUp()
{
type = GET_PARAM(0);
channels = GET_PARAM(1);
use_roi = GET_PARAM(2);
cv::Size size(MWIDTH, MHEIGHT);
for (int i = 0; i < channels; ++i)
mat[i] = randomMat(size, CV_MAKETYPE(type, 1), 5, 16, false);
dst = randomMat(size, CV_MAKETYPE(type, channels), 5, 16, false);
}
void random_roi()
{
if (use_roi)
{
//randomize ROI
roicols = rng.uniform(1, mat[0].cols);
roirows = rng.uniform(1, mat[0].rows);
for (int i = 0; i < channels; ++i)
{
srcx[i] = rng.uniform(0, mat[i].cols - roicols);
srcy[i] = rng.uniform(0, mat[i].rows - roirows);
}
dstx = rng.uniform(0, dst.cols - roicols);
dsty = rng.uniform(0, dst.rows - roirows);
}
else
{
roicols = mat[0].cols;
roirows = mat[0].rows;
for (int i = 0; i < channels; ++i)
srcx[i] = srcy[i] = 0;
dstx = dsty = 0;
}
for (int i = 0; i < channels; ++i)
mat_roi[i] = mat[i](Rect(srcx[i], srcy[i], roicols, roirows));
dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
for (int i = 0; i < channels; ++i)
gmat[i] = mat_roi[i];
}
};
struct Merge : MergeTestBase {};
OCL_TEST_P(Merge, Accuracy)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::merge(mat_roi, channels, dst_roi);
cv::ocl::merge(gmat, channels, gdst);
EXPECT_MAT_NEAR(dst, Mat(gdst_whole), 0.0);
}
}
PARAM_TEST_CASE(SplitTestBase, MatType, int, bool)
{
int type;
int channels;
bool use_roi;
cv::Mat src, src_roi;
cv::Mat dst[MAX_CHANNELS], dst_roi[MAX_CHANNELS];
cv::ocl::oclMat gsrc_whole, gsrc_roi;
cv::ocl::oclMat gdst_whole[MAX_CHANNELS], gdst_roi[MAX_CHANNELS];
virtual void SetUp()
{
type = GET_PARAM(0);
channels = GET_PARAM(1);
use_roi = GET_PARAM(2);
}
void random_roi()
{
Size roiSize = randomSize(1, MAX_VALUE);
Border srcBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, roiSize, srcBorder, CV_MAKETYPE(type, channels), 0, 256);
generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
for (int i = 0; i < channels; ++i)
{
Border dstBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
randomSubMat(dst[i], dst_roi[i], roiSize, dstBorder, CV_MAKETYPE(type, 1), 5, 16);
generateOclMat(gdst_whole[i], gdst_roi[i], dst[i], roiSize, dstBorder);
}
}
};
struct Split : SplitTestBase {};
OCL_TEST_P(Split, Accuracy)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::split(src_roi, dst_roi);
cv::ocl::split(gsrc_roi, gdst_roi);
for (int i = 0; i < channels; ++i)
{
EXPECT_MAT_NEAR(dst[i], gdst_whole[i], 0.0);
EXPECT_MAT_NEAR(dst_roi[i], gdst_roi[i], 0.0);
}
}
}
INSTANTIATE_TEST_CASE_P(SplitMerge, Merge, Combine(
Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F), Values(1, 2, 3, 4), Bool()));
INSTANTIATE_TEST_CASE_P(SplitMerge, Split , Combine(
Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F), Values(1, 2, 3, 4), Bool()));
#endif // HAVE_OPENCL